Interface and results visualization of WMN-GA simulation system: Evaluation for Exponential and Weibull distributions considering different transmission rates
Introduction
The Wireless Mesh Networks (WMNs) are currently attracting a lot of attention due to their importance for providing cost-efficient broadband wireless connectivity. The WMNs can be seen as a special type of wireless ad-hoc networks.
WMNs are based on mesh topology, in which every node (representing a server) is connected through wireless links to one or more nodes, enabling thus the information transmission in more than one path. The path redundancy is a robust feature of mesh topology. Compared to other topologies, mesh topology does not need a central node, allowing networks based on it to be self-healing. These characteristics of networks with mesh topology make them very reliable and robust networks to potential server node failures.
There are a number of application scenarios for which the use of WMNs is a very good alternative to offer connectivity at a low cost. It should also mentioned that there are applications of WMNs which are not supported directly by other types of wireless networks such as cellular networks, ad hoc networks, wireless sensor networks, and standard IEEE 802.11 networks. There are many applications of WMNs in Neighboring Community Networks, Corporative Networks, Metropolitan Area Networks, Transportation Systems, Automatic Control Buildings, Medical and Health Systems, Surveillance and so on.
In WMNs, the mesh routers provide network connectivity services to mesh client nodes. The good performance and operability of WMNs largely depends on placement of mesh router nodes in the geographical deployment area to achieve network connectivity, stability, and client coverage.
In this work, we present the interface of WMN-GA system, which is based on Genetic Algorithms (GAs). We evaluate the performance of WMN-GA simulation system for Exponential and Weibull distributions considering different transmission rates. We present the visualization of the simulation results for different generations. As evaluation parameters, we consider the Packet Delivery Ratio (PDR), throughput and delay metrics. For simulations, we use ns-3 simulator and Hybrid Wireless Mesh Protocol (HWMP).
The structure of the paper is as follows. In Section 2, we discuss the related work. In Section 3, we make an overview of HWMP routing protocol. In Section 4, we present the implemented WMN-GA simulation system. In Section 5, we show the description of ns-3 and path loss model. In Section 6, we show the simulation results. Finally, conclusions and future work are given in Section 7.
Section snippets
Related work
Until now, many researchers performed valuable research in the area of multi-hop wireless networks by computer simulations and experiments [1]. Most of them are focused on throughput improvement and they do not consider mobility [2].
Several heuristic approaches are found in the literature for node placement problems in WMNs [3], [4], [5].
In [3], the authors investigate the role of gateway placement on network throughput for realistic configurations of WMNs. They show that the position of the
Overview of HWMP routing protocol
The IEEE 802.11s draft defines a default routing protocol called the Hybrid Wireless Mesh Protocol (HWMP). Every IEEE 802.11s compliant device is required to implement HWMP and to be capable of using it. HWMP is located on layer 2, this means, it uses MAC addresses.
The nodes of a WMN are called Mesh Points (MPs) in IEEE 802.11s. A MP is an IEEE 802.11 station that has mesh capabilities in addition to the basic station functionality. This means that it can participate in the mesh routing
Implemented WMN-GA simulation system
The proposed and implemented WMN-GA system is based on GA. In this section, we present briefly GA and then the proposed WMN-GA simulation system.
ns-3
The ns-3 simulator is developed and distributed completely in the C++ programming language, because it better facilitated the inclusion of C-based implementation code. The ns-3 architecture is similar to Linux computers, with internal interface and application interfaces such as network interfaces, device drivers and sockets. The goals of ns-3 are set very high: to create a new network simulator aligned with modern research needs and develop it in an open source community. Users of ns-3 are
Simulation results
In this section, we present the simulation results. We use WMN-GA system for node placement problem in WMNs. A bi-objective optimization is used to solve this problem by first maximizing the number of connected routers in the network and then the client coverage. The input parameters of WMN-GA system are shown in Table 1. The area size is considered 640 m × 640 m (or 32 units × 32 units). The number of mesh routers is 16 and the number of mesh clients is 48. We used HWMP routing protocol and sent
Conclusions
In this paper, we presented the interface of WMN-GA system and evaluated the performance of WMN-GA simulation system for Exponential and Weibull distributions considering different transmission rates. We present the visualization of the simulation results for different generations. As evaluation parameters, we considered the PDR, throughput and delay metrics. For simulations, we use ns-3 simulator and Hybrid Wireless Mesh Protocol (HWMP). The topologies of WMN are generated using WMN-GA system
Acknowledgment
This work is supported by a Grant-in-Aid for Scientific Research from Japanese Society for the Promotion of Science (JSPS). The authors would like to thank JSPS for the financial support.
References (17)
- et al.
k-Center problems with minimum coverage
Theor. Comput. Sci.
(2005) APE — a Large Scale Ad Hoc Network Testbed for Reproducible Performance Tests
(2002)- et al.
Comparison of routing metrics for static multi-hop wireless networks
- et al.
Single gateway placement in wireless mesh networks
Gateways placement in backbone wireless mesh networks
Int. J. Commun. Netw. Syst. Sci.
(2009)- et al.
Node placement algorithm for deployment of two-tier wireless mesh networks
- et al.
Efficient mesh router placement in wireless mesh networks
- et al.
Genetic algorithm to optimize node placement and configuration for WLAN planning